[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"news-73b75304-841d-4465-83ee-63eedfa96bee":3},{"id":4,"title":5,"summary":6,"original_url":7,"source_id":8,"tags":9,"published_at":23,"created_at":24,"modified_at":25,"is_published":26,"publish_type":27,"image_url":13,"view_count":28},"73b75304-841d-4465-83ee-63eedfa96bee","阿里云发布真武M890：128卡超节点瞄准Agent并发推理","5月20日，在2026阿里云峰会上，阿里发布基于平头哥新一代AI芯片真武M890的128卡超节点服务器。该服务器搭载互联芯片ICN Switch 1.0，通信时延低至百纳秒级，可将128张AI芯片组成一台统一调度的计算集群，旨在满足Agentic时代海量并发推理与大模型训练的双重需求。\n\n传统大模型训练与推理在芯片层面往往面临通信带宽的瓶颈——当跨节点协作成为常态时，机间通信延迟会直接抵消算力扩展的收益。真武M890通过自研ICN Switch 1.0在互联层实现百纳秒级时延，意味着128卡之间的数据交换几乎可以做到无等待协同。这对需要频繁跨节点传递注意力权重或KV Cache的Transformer模型尤为关键。\n\n从系统架构角度看，阿里云这套128卡超节点的思路与NVIDIA日前交付的Agent专用CPU Vera形成了有趣的呼应：NVIDIA从处理器层面重新思考Agent场景下的并发调度，阿里则从互联层面解决多芯片协作的通信死角。两者都在解决同一个根本问题——当AI工作负载从单模型推理转向多Agent并发时，既有的基础设施假设已经不够用了。\n\n值得关注的是，这是平头哥芯片首次在超节点尺度上实现产品化落地。从倚天CPU到含光NPU再到真武M890，平头哥的芯片迭代路径正在从单芯片性能优化走向系统级协同设计。对于国内AI基础设施的自主可控而言，真武M890的集群方案是一个值得持续跟踪的进展。","https:\u002F\u002F36kr.com\u002Fnewsflashes\u002F3817018077447040","5e4fd3d1-9cb4-44a6-bae5-9ffb449c05c1",[10,14,17,20],{"id":11,"name":12,"slug":12,"description":13,"color":13},"a8002d98-9df1-4ab9-94d4-a7625af634c4","china-ai",null,{"id":15,"name":16,"slug":16,"description":13,"color":13},"e0d31e94-ce47-4c8f-831c-d3d2926d42f3","hardware",{"id":18,"name":19,"slug":19,"description":13,"color":13},"0a93ec8e-ea39-4693-81de-563ca8c173f7","inference",{"id":21,"name":22,"slug":22,"description":13,"color":13},"b1853a5a-d940-42b7-94f9-0488ee3f2cf7","new-model","2026-05-20T04:15:00Z","2026-05-20T04:11:51.286643Z","2026-05-20T04:11:51.286653Z",true,"agent",3]